Jorge Laureano Moya Rodríguez – Neural Networks – Best Researcher Award

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Jorge Laureano Moya Rodríguez – Neural Networks

 Prof Dr.  Jorge Laureano Moya Rodríguez distinguished academic and researcher in the field Neural Network.  Jorge Laureano Moya Rodríguez is a Professor Emeritus at the Central University “Marta Abreu” de las Villas. Cuba. He received his Ph.D. in Mechanical Engineering at this university in 1994. He published over a three hundred papers in professional journals and he has authored several books in mechanical and electrical engineering. He has several international and national awards, including some from the Academy of Sciences of Cuba. He has lectured in different Universities of Spain, México, Nicaragua and Brazil. He is currently visiting professor at the Federal University of Bahia in Brazil. Dr. Moya’s research interests are Multiobjective Optimization, Logistics, Computer Aided Design, and Computer Aided Engineering.

Ele é também membro da ERASMUS MUNDUS ASSOCIATION (EMA) e da Associação Mexicana de Modelagem Numérica e Engenharia (AMMNI). Reconhecido como bolsista de produtividade em Pesquisa pelo CNPq (nível 2) e consultor ad hoc do CNPq, ele contribui como árbitro para diversas revistas científicas e instituições acadêmicas em países como Venezuela, Colômbia, Peru e Cuba. Com uma ampla lista de mais de 50 projetos de pesquisa concluídos e implementados em Cuba, ele é considerado Professor de Mérito pela Universidade Central Marta Abreu de Las Villas. Sua atuação como professor abrange cursos de pós-graduação e disciplinas de mestrado em várias universidades, incluindo a Universidade Federal do Espírito Santo (Brasil), Universidade Veracruzana (México), Universidade Técnica do Estado de Aragua (Venezuela) e Universidade Nacional de Engenharia (Nicarágua). Ele também coordenou o Mestrado em Engenharia Mecatrônica em várias universidades na Venezuela e trabalhou como professor convidado em diversas instituições no México, Peru e Espanha. Anteriormente, ele foi pesquisador do ITEGAM, professor visitante na Universidade Federal do Espírito Santo e na Universidade Federal da Bahia.

 

🌐 Professional Profiles

Educations: 📚🎓

Jorge Laureano Moya Rodríguez, known in bibliographic citations as J. L. M. Rodríguez, J. L. Moya, Jorge Moya, Jorge Laureano Moya Rodríguez, J. Moya, Jorge Rodríguez, Jorge L. Moya Rodríguez, or variations thereof, is affiliated with the University Federal da Bahia, where he works within the Program of Industrial Engineering Postgraduate Studies.

He completed a postdoctoral position in 2011 at the Universidad de Oviedo, UNIOVI, Spain, funded by the Agencia Española de Colaboración Internacional, AECI, Spain. The research was in the field of Engineering.

In 2008, he undertook a postdoctoral fellowship at the Universidad de Oviedo, UNIOVI, Spain, funded by ERASMUS MUNDUS, EM, Germany. The research focus was in Engineering.

In 2005, he conducted postdoctoral research at the Universidad Católica de Leuven, KLU, Belgium, supported by VLIR, VLIR, Belgium. The research was within the field of Engineering.

Publication

 

Tumlumbe Juliana Chengula – Computer Vision -Best Researcher Award

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Tumlumbe Juliana Chengula  – Computer Vision

Tumlumbe Juliana Chengula  a distinguished academic and researcher in the field of Computer Vision. He possesses proficiency in several programming languages, with a focus on Python. His expertise extends to utilizing various tools such as Tableau, QGIS, PyTorch, and Tensorflow, showcasing a well-rounded skill set in data science and machine learning. Additionally, he has earned certifications in Data Science Tools, SQL for Data Science, and Machine Learning with Python, all from IBM. Furthermore, he has completed the “Using Python for Research” certification from Harvard University, underscoring his commitment to continuous learning and staying at the forefront of relevant technologies in the field. These skills and honors collectively highlight his comprehensive knowledge and dedication to the dynamic and evolving realm of data science.

Eduvation

His master’s studies at Amirkabir University of Technology (AUT) in Tehran, Iran, from September 2018 to October 2021, he specialized in Electrical Engineering with a focus on Control. During this period, he maintained a GPA of 3.5/4, and his final project earned a perfect score of 4/4. Prior to his master’s degree, he completed his Bachelor’s in Power Electrical Engineering at Yazd University, Iran, from September 2014 to August 2018, achieving a GPA of 3.1/4.

Professional Profiles:

Employment Experience
As a Graduate Research Assistant at South Carolina State University since August 2022, she has been actively engaged in the collection, recording, and analysis of transportation data, utilizing proficient tools such as Python, Tableau, PowerBI, and QGIS. Her research focus involves the application of cutting-edge technologies, including Machine Learning, Deep Learning, and Artificial Intelligence, to address challenges within the transportation industry.
Over the course of her tenure, she has showcased her contributions by delivering six impactful presentations on her research in Machine Learning and Artificial Intelligence at seven distinguished transportation conferences. Furthermore, her commitment to scholarly dissemination is evident through the submission and acceptance of two peer-reviewed articles, which are slated for presentation at the prestigious 2024 Annual Transportation Research Board conference. These accomplishments underscore her dedication to advancing knowledge and providing innovative solutions to enhance the efficiency and effectiveness of the transportation sector.
Research Project Highlights
She has made notable contributions to the field of transportation through her research endeavors, addressing critical issues with cutting-edge technologies. One of her significant projects involves enhancing road safety through Ensemble Learning, specifically in detecting driver anomalies using vehicle inbuilt cameras. In another study, she employed Topic Modeling and Categorical Correlations to unveil patterns associated with autonomous vehicle disengagements, shedding light on crucial aspects of autonomous driving systems.
Furthermore, she delved into the realm of quantum computing to improve classification performance in traffic sign recognition, utilizing an optimized hybrid classical-quantum approach. Additionally, her research extends to the realm of sustainable urban mobility, where she has applied Explainable Artificial Intelligence to predict bike-sharing station capacity. These diverse projects showcase her proficiency in utilizing advanced technologies and methodologies to address multifaceted challenges within the transportation sector.
Publication

Improving road safety with ensemble learning: Detecting driver anomalies using vehicle inbuilt cameras

Machine Learning with Applications
2023-12 | Journal article
DOI: 10.1016/j.mlwa.2023.100510
CONTRIBUTORS: Tumlumbe Juliana Chengula; Judith Mwakalonge; Gurcan Comert; Saidi Siuhi

Sankar Shanmuganathan – Generative adversarial networks

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Dr. Sankar Shanmuganathan – Leading Researcher in Generative adversarial networks

Dr.  Sankar Shanmuganathan  a distinguished academic and researcher in the field of Generative adversarial networks. He is currently serving as a Professor in the Department of Computer Science and Engineering at Saveetha School of Engineering, SIMATS, Chennai, Tamil Nadu, India. A dedicated, resourceful, and goal-driven professional educator, he is passionate about programming and has a solid commitment to academic growth. With over 20 years of experience, he is a seasoned researcher and has taught courses for both undergraduate and postgraduate students. He has successfully supervised 20 Bachelor’s theses and 10 Master’s theses, demonstrating his mentorship skills. His contributions extend to publishing articles in peer-reviewed journals and conferences, obtaining three patents, and securing grants from AICTE for organizing technical events.🌟💻🔬

Eduvation

He completed his Ph.D. in Information Technology from Hindustan University in 2018. 🎓 Prior to that, he earned a Master’s degree in Software Engineering from Periyar Maniammai College of Technology, affiliated with Anna University, Chennai, Tamil Nadu, in 2006, achieving a first-class distinction. 🏆 His academic journey began with a Bachelor’s degree in Computer Engineering from Arulmigu Kalasalingam College of Engineering, Srivilliputhur, Tamil Nadu, in 1992, where he also excelled with a first-class distinction. 🏅 This degree was affiliated with Madurai Kamaraj University, Madurai, Tamil Nadu. 🌟

Professional Profiles:

RESEARCH ACTIVITIES

🗣️He has obtained three patents from IP Australia, showcasing his innovative contributions. The first patent, dated October 27, 2021 (Patent No: 2021102955), is titled “A System and Method for Agile Meeting Dashboard.” The second patent, dated May 5, 2021 (Patent No: 2021101703), pertains to “3D Printing of Cost-Effective Human Skull Models and Skull Implants.” The third patent, dated April 7, 2021 (Patent No: 2021100286), is for “Aqua Life: A Compact Device Extracting Drinkable Water from Sea Water.”

In addition to his research achievements, he has undertaken various consultancy projects. Notably, he developed a software product for MEL Systems and Services Ltd, Chennai, involving the creation of advanced reports using Python, Django, and MongoDB. Another significant project involved the development of a software product to detect glaucoma in optical coherence tomography images for M/s Appasamy Associates R & D, Chennai, implemented in Java and Matlab.

Furthermore, he contributed to software bug fixing for General Electricals T & D Limited, Chennai, utilizing VB.NET technology. Additionally, he conducted corporate training for General Electricals T & D Limited, Chennai, imparting VB.NET platform skills to GE employees, preparing them to independently develop utility software. The funds received for training amounted to Rs. 2,00,000. Overall, his diverse expertise and accomplishments reflect his commitment to both innovation and practical application in the field.

BOOKS AUTHORED / CHAPTER CONTRIBUTED

AUTHORED BOOK on OBJECT ORIENTED PROGRAMMING Published by Laxmi PublicationsChennai,
2009
CHAPTER CONTRIBUTED LEAN SIX SIGMA: SIX SIGMA PROJECTS AND PERSONAL EXPERIENCEPublished by In-Tech Open Access Publications, Crotia, 2012

RESEARCH PAPERS PUBLISHED

  • Deep generative adversarial networks with marine predators algorithm for classification of Alzheimer’s disease using electroencephalogram
    • Authors: J.C. Sekhar, Ch Rajyalakshmi, S. Nagaraj, S. Sankar, Rajesh Saturi, A. Harshavardhan
    • Published in: Journal of King Saud University – Computer and Information Sciences
    • Volume 35, Issue 10, December 2023
    • DOI: 10.1016/j.jksuci.2023.101848
  • Exploration of Performance of Dynamic Branch Predictors used in Mitigating Cost of Branching
    • Authors: Akash Ambashankar, Ganesh Chandrasekar, AR Charan, S Sankar
    • Published in: 2022 IEEE Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)
  • AI Enabled Educational Bot to Improve Learning Outcomes using Bag of Words Algorithm
  • Intelligent Organ Transplantation System Using Rank Search Algorithm to Serve Needy Recipients
    • Authors: S Sankar, U Shuruti, B Bhuvaneshwari
    • Published in: 2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES)
  • Understanding Query Intention in Search Queries of Learners in Blended Learning Environments
    • Authors: Vivekananthamoorthy Natarajan, Sankar Shanmuganathan
    • Published in: 2022 IEEE 4th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA)
  • Sign language translator using YOLO algorithm
    • Authors: Bhavadharshini, M., Josephine Racheal, J., Kamali, M., Sankar, S.
    • Published in: Advances in Parallel Computing, 2021, 39, pp. 159-166
  • Detection of Anomalous Behaviour in Online Exam towards Automated Proctoring
    • Authors: Susithra V, Resham A, Bishruti Gope, Sankar
    • Published in: IEEE International Conference on System, Computation, Automation and Networking
    • DOI: 10.1109/ICSCAN53069.2021.9526448
  • Development of Novel Technique to Detect and Validate Pulmo Malignancy during Early Stages
    • Authors: Dhanalakshmi R, Shree Harini R, Pravallika M, S Sankar
    • Published in: International Journal of Current Research and Review, volume: 13 issue: 17, pp. 56-60, 12th September 2021
    • DOI: http://dx.doi.org/10.31782/IJCRR.2021.131711
  • Sentiment Analysis of Twitter Political Data using GRU Neural Network
    • Authors: Seenaiah Pedipina, Sankar S and R Dhanalakshmi
    • Published in: International Journal of Advanced Science and Technology 29(6), pp. 5307-5320, ISSN 2207-6360, SERSC Australia
  • Sentimental Analysis On Twitter Data Of Political Domain
    • Authors: Seenaiah Pedipina, Sankar S and R Dhanalakshmi
    • Published in: Dogo Rangsang Research Journal, UGC Care Group I Journal, Vol-10 Issue-07 No. 16 July 2020, ISSN:2347-7180
  • An Improved Framework for Sentiment Analysis for College Reviews
    • Authors: T. Sri Devi, R. Dhanalakshmi, S. Sankar
    • Published in: International Journal of Advanced Trends in Computer Science and Engineering, 9(2), 1959-1963